Tracking moving objects is a critical skill for many everyday tasks, such as crossing a busy street, driving a car or catching a ball. Attention is a key cognitive function that supports object tracking; however, our understanding of the brain mechanisms that support attention is almost exclusively based on evidence from tasks that present stable objects at fixed locations. Accounts of multiple object tracking are also limited because they are largely based on behavioral data alone and involve tracking objects in a 2D plane. Consequently, the neural mechanisms that enable moment-by-moment tracking of goal-relevant objects remain poorly understood. To address this knowledge gap, we developed SABER (Spatial Attention, Brain, Extended Reality), a new framework for studying the behavioral and neural dynamics of attention to objects moving in 3D. Participants (n=32) completed variants of a task inspired by the popular virtual reality (VR) game, Beat Saber, where they used virtual sabers to strike stationary and moving color-defined target spheres while we recorded electroencephalography (EEG). We first established that standard univariate EEG metrics which are typically used to study spatial attention to static objects presented on 2D screens, can generalize effectively to an immersive VR context involving both static and dynamic 3D stimuli. We then used a computational modeling approach to reconstruct moment-by-moment attention to the locations of stationary and moving objects from oscillatory brain activity, demonstrating the feasibility of precisely tracking attention in a 3D space. These results validate SABER, and provide a foundation for future research that is critical not only for understanding how attention works in the physical world, but is also directly relevant to the development of better VR applications.

翻译：追踪移动物体是许多日常任务（如穿越繁忙街道、驾驶汽车或接住球）中的关键技能。注意力是支持物体追踪的核心认知功能；然而，我们对支撑注意力的脑机制的理解几乎完全基于在固定位置呈现稳定物体的任务证据。多物体追踪的研究也因主要依赖行为数据且涉及二维平面追踪而受到限制。因此，逐时刻追踪目标相关物体的神经机制仍知之甚少。为填补这一知识空白，我们开发了SABER（空间注意力、大脑、扩展现实）新框架，用于研究注意三维空间中移动物体的行为与神经动力学。参与者（n=32）完成了受流行虚拟现实游戏《节奏光剑》启发的一系列变体任务：他们使用虚拟光剑击打静止和移动的颜色定义目标球体，同时记录脑电图。我们首先证实，常用于研究二维屏幕上静态物体空间注意的标准单变量脑电图指标，能有效推广到涉及静态与动态三维刺激的沉浸式虚拟现实场景。随后采用计算建模方法，从振荡性脑活动中逐时刻重建对静止和移动物体位置的注意力，证明精确追踪三维空间注意力的可行性。这些结果验证了SABER框架，为未来的研究奠定基础——不仅对理解物理世界中的注意力机制至关重要，也与开发更优质的虚拟现实应用直接相关。